Defuzzification of the initial context in Formal Concept Analysis

The research field is the problem of extracting from the initial empirical material the formal concept lattice, which can serve as the basis of the formal ontology of the studied subject domain. The initial empirical material, i.e. the data of multidimensional observations and experiments, is characterized by incompleteness and inconsistency, conditioned by realities of empirical information accumulation. This leads to the fact that required for lattice building formal context can be previously presented only within the framework of some multivalued logic. It needs to be approximated in binary logic, since effective methods for derivation of formal concepts are developed only for unambiguous (binary) formal contexts. The exact solution of this problem, considering the properties existence constraints of objects in the studied subject domain, is difficult and in a certain sense is inadequate to expectations of subject exploring the subject domain. For defuzzification of the initial formal context heuristic was proposed, idea of which is to localize the approximation task of "soft" context within every group of dependent properties of each object of learning sample. The model reflecting such restrictions is formed as hierarchy of groups of dependent properties, which predetermines the recursive and multi-pass nature of the developed defuzzification algorithm.